Overview

Dataset statistics

Number of variables14
Number of observations52704
Missing cells8205
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 MiB
Average record size in memory112.0 B

Variable types

DateTime1
Numeric13

Alerts

Power (kW) is highly overall correlated with Rear bearing temperature (°C) and 6 other fieldsHigh correlation
Wind direction (°) is highly overall correlated with Nacelle position (°)High correlation
Nacelle position (°) is highly overall correlated with Wind direction (°)High correlation
blade_angle is highly overall correlated with Rear bearing temperature (°C)High correlation
Rear bearing temperature (°C) is highly overall correlated with Power (kW) and 5 other fieldsHigh correlation
Rotor speed (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Generator RPM (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Front bearing temperature (°C) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Tower Acceleration X (mm/ss) is highly overall correlated with Power (kW) and 4 other fieldsHigh correlation
Wind speed (m/s) is highly overall correlated with Power (kW) and 5 other fieldsHigh correlation
Tower Acceleration y (mm/ss) is highly overall correlated with Power (kW) and 5 other fieldsHigh correlation
blade_angle has 748 (1.4%) missing valuesMissing
Rear bearing temperature (°C) has 748 (1.4%) missing valuesMissing
Nacelle ambient temperature (°C) has 748 (1.4%) missing valuesMissing
Front bearing temperature (°C) has 748 (1.4%) missing valuesMissing
Tower Acceleration X (mm/ss) has 749 (1.4%) missing valuesMissing
Tower Acceleration y (mm/ss) has 749 (1.4%) missing valuesMissing
Metal particle count counter has 749 (1.4%) missing valuesMissing
# Date and time has unique valuesUnique
blade_angle has 17809 (33.8%) zerosZeros
Rotor speed (RPM) has 2032 (3.9%) zerosZeros

Reproduction

Analysis started2023-07-08 11:58:34.887003
Analysis finished2023-07-08 11:58:53.199847
Duration18.31 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

Distinct52704
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size411.9 KiB
Minimum2020-01-01 00:00:00
Maximum2020-12-31 23:50:00
2023-07-08T17:28:53.248074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:53.347459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Power (kW)
Real number (ℝ)

Distinct52156
Distinct (%)99.9%
Missing495
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean657.28454
Minimum-14.172914
Maximum2079.8706
Zeros3
Zeros (%)< 0.1%
Negative6715
Negative (%)12.7%
Memory size411.9 KiB
2023-07-08T17:28:53.566568image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-14.172914
5-th percentile-2.6626985
Q1113.04459
median407.91578
Q31065.0568
95-th percentile2019.0777
Maximum2079.8706
Range2094.0435
Interquartile range (IQR)952.01219

Descriptive statistics

Standard deviation661.98608
Coefficient of variation (CV)1.007153
Kurtosis-0.52628313
Mean657.28454
Median Absolute Deviation (MAD)370.8122
Skewness0.89578917
Sum34316168
Variance438225.56
MonotonicityNot monotonic
2023-07-08T17:28:53.657301image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-2.180000067 3
 
< 0.1%
0 3
 
< 0.1%
-0.8215900272 2
 
< 0.1%
-3.019999981 2
 
< 0.1%
-0.8491073972 2
 
< 0.1%
-1.636244541 2
 
< 0.1%
-1.383899027 2
 
< 0.1%
-1.195040032 2
 
< 0.1%
-1.807498032 2
 
< 0.1%
-1.314010534 2
 
< 0.1%
Other values (52146) 52187
99.0%
(Missing) 495
 
0.9%
ValueCountFrequency (%)
-14.17291357 1
< 0.1%
-14.10135505 1
< 0.1%
-13.54592905 1
< 0.1%
-13.39493456 1
< 0.1%
-13.32203399 1
< 0.1%
-13.28043208 1
< 0.1%
-13.18747443 1
< 0.1%
-13.02889207 1
< 0.1%
-13.01834704 1
< 0.1%
-12.52681661 1
< 0.1%
ValueCountFrequency (%)
2079.870593 1
< 0.1%
2076.975914 1
< 0.1%
2076.478369 1
< 0.1%
2076.423468 1
< 0.1%
2076.341827 1
< 0.1%
2075.217114 1
< 0.1%
2075.193622 1
< 0.1%
2074.198071 1
< 0.1%
2074.033447 1
< 0.1%
2073.855566 1
< 0.1%

Wind direction (°)
Real number (ℝ)

Distinct52210
Distinct (%)100.0%
Missing494
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean199.0089
Minimum0.021386067
Maximum359.98372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:53.752213image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.021386067
5-th percentile30.193634
Q1145.29004
median220.72748
Q3262.01798
95-th percentile326.96947
Maximum359.98372
Range359.96234
Interquartile range (IQR)116.72793

Descriptive statistics

Standard deviation91.493962
Coefficient of variation (CV)0.4597481
Kurtosis-0.64927738
Mean199.0089
Median Absolute Deviation (MAD)48.58127
Skewness-0.56738345
Sum10390254
Variance8371.1451
MonotonicityNot monotonic
2023-07-08T17:28:53.849212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
179.5196263 1
 
< 0.1%
178.8793547 1
 
< 0.1%
176.4490078 1
 
< 0.1%
177.1054822 1
 
< 0.1%
187.9436167 1
 
< 0.1%
182.0154968 1
 
< 0.1%
176.9800539 1
 
< 0.1%
168.0959476 1
 
< 0.1%
168.9335407 1
 
< 0.1%
172.154464 1
 
< 0.1%
Other values (52200) 52200
99.0%
(Missing) 494
 
0.9%
ValueCountFrequency (%)
0.02138606697 1
< 0.1%
0.02279681144 1
< 0.1%
0.03558196345 1
< 0.1%
0.04241570585 1
< 0.1%
0.06772473222 1
< 0.1%
0.1008395459 1
< 0.1%
0.1026826659 1
< 0.1%
0.1083003876 1
< 0.1%
0.1102384044 1
< 0.1%
0.1132206686 1
< 0.1%
ValueCountFrequency (%)
359.9837222 1
< 0.1%
359.9742812 1
< 0.1%
359.9688544 1
< 0.1%
359.9576409 1
< 0.1%
359.9525294 1
< 0.1%
359.9340244 1
< 0.1%
359.9321337 1
< 0.1%
359.9201797 1
< 0.1%
359.8816266 1
< 0.1%
359.861649 1
< 0.1%

Nacelle position (°)
Real number (ℝ)

Distinct13983
Distinct (%)26.8%
Missing494
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean198.98439
Minimum0.03444581
Maximum359.76303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:53.956594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.03444581
5-th percentile29.545336
Q1147.19086
median220.7272
Q3263.53339
95-th percentile326.09412
Maximum359.76303
Range359.72859
Interquartile range (IQR)116.34253

Descriptive statistics

Standard deviation91.897153
Coefficient of variation (CV)0.46183097
Kurtosis-0.65358387
Mean198.98439
Median Absolute Deviation (MAD)49.391571
Skewness-0.57197521
Sum10388975
Variance8445.0867
MonotonicityNot monotonic
2023-07-08T17:28:54.053184image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203.1661682 607
 
1.2%
147.1908569 155
 
0.3%
215.2405396 150
 
0.3%
216.3381042 146
 
0.3%
252.5577393 143
 
0.3%
258.0455627 143
 
0.3%
259.1425781 129
 
0.2%
189.9958801 123
 
0.2%
227.3137512 120
 
0.2%
48.41065598 118
 
0.2%
Other values (13973) 50376
95.6%
(Missing) 494
 
0.9%
ValueCountFrequency (%)
0.03444581008 1
 
< 0.1%
0.04504445738 1
 
< 0.1%
0.1179816723 14
 
< 0.1%
0.1184692383 9
 
< 0.1%
0.1185302734 15
 
< 0.1%
0.1185405329 15
 
< 0.1%
0.1185607985 59
0.1%
0.1186218262 1
 
< 0.1%
0.1190795973 2
 
< 0.1%
0.1827026913 1
 
< 0.1%
ValueCountFrequency (%)
359.7630313 1
< 0.1%
359.6601242 1
< 0.1%
359.483398 1
< 0.1%
359.4308563 1
< 0.1%
359.4109822 1
< 0.1%
359.3435693 1
< 0.1%
359.3139604 1
< 0.1%
359.283881 1
< 0.1%
359.083013 1
< 0.1%
359.0341896 1
< 0.1%

blade_angle
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct21085
Distinct (%)40.6%
Missing748
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean8.2974115
Minimum0
Maximum94.704396
Zeros17809
Zeros (%)33.8%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:54.157824image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.2485
Q32.2458264
95-th percentile44.996667
Maximum94.704396
Range94.704396
Interquartile range (IQR)2.2458264

Descriptive statistics

Standard deviation20.051991
Coefficient of variation (CV)2.4166562
Kurtosis7.7957988
Mean8.2974115
Median Absolute Deviation (MAD)0.2485
Skewness2.8856699
Sum431100.31
Variance402.08234
MonotonicityNot monotonic
2023-07-08T17:28:54.251487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17809
33.8%
44.99666723 3345
 
6.3%
1.49666667 973
 
1.8%
89.99666595 869
 
1.6%
0.02483333349 586
 
1.1%
77.06666692 472
 
0.9%
92.40999858 387
 
0.7%
0.04966666698 253
 
0.5%
1.49666667 207
 
0.4%
0.07450000048 143
 
0.3%
Other values (21075) 26912
51.1%
(Missing) 748
 
1.4%
ValueCountFrequency (%)
0 17809
33.8%
0.0001666666622 12
 
< 0.1%
0.0001666666629 7
 
< 0.1%
0.0001754385926 4
 
< 0.1%
0.000196078427 1
 
< 0.1%
0.0003333333201 2
 
< 0.1%
0.0003333333244 5
 
< 0.1%
0.0003333333259 12
 
< 0.1%
0.0003508771836 1
 
< 0.1%
0.0003508771851 4
 
< 0.1%
ValueCountFrequency (%)
94.70439608 1
 
< 0.1%
92.53666687 1
 
< 0.1%
92.53333282 1
 
< 0.1%
92.52333323 1
 
< 0.1%
92.52333323 4
 
< 0.1%
92.51999664 1
 
< 0.1%
92.51666768 1
 
< 0.1%
92.51666514 1
 
< 0.1%
92.49666595 71
0.1%
92.46333313 15
 
< 0.1%

Rear bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39119
Distinct (%)75.3%
Missing748
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean63.00369
Minimum9.5142858
Maximum75.907501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:54.347391image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum9.5142858
5-th percentile36.2575
Q163.2775
median67.079583
Q368.98
95-th percentile71.1775
Maximum75.907501
Range66.393215
Interquartile range (IQR)5.7025

Descriptive statistics

Standard deviation11.682941
Coefficient of variation (CV)0.18543265
Kurtosis7.4224986
Mean63.00369
Median Absolute Deviation (MAD)2.3704175
Skewness-2.7099172
Sum3273419.7
Variance136.49112
MonotonicityNot monotonic
2023-07-08T17:28:54.439646image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.60000038 12
 
< 0.1%
14.30000019 11
 
< 0.1%
13.80000019 11
 
< 0.1%
67.38750038 11
 
< 0.1%
14.89999962 10
 
< 0.1%
69.01999969 10
 
< 0.1%
14.39999962 9
 
< 0.1%
69.51500015 9
 
< 0.1%
68.14749985 9
 
< 0.1%
68.98000031 9
 
< 0.1%
Other values (39109) 51855
98.4%
(Missing) 748
 
1.4%
ValueCountFrequency (%)
9.514285769 1
< 0.1%
9.571052903 1
< 0.1%
9.582500267 1
< 0.1%
9.597500229 1
< 0.1%
9.600000381 1
< 0.1%
9.6625 1
< 0.1%
9.674999952 1
< 0.1%
9.67750001 1
< 0.1%
9.680000114 1
< 0.1%
9.682499886 1
< 0.1%
ValueCountFrequency (%)
75.90750084 1
< 0.1%
74.94500084 1
< 0.1%
74.88750076 1
< 0.1%
74.88250046 1
< 0.1%
74.81842202 1
< 0.1%
74.75499878 1
< 0.1%
74.66749916 1
< 0.1%
74.65499649 1
< 0.1%
74.62352663 1
< 0.1%
74.61749725 1
< 0.1%

Rotor speed (RPM)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct49951
Distinct (%)95.7%
Missing495
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean10.503876
Minimum0
Maximum15.328223
Zeros2032
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:54.542959image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.091564157
Q19.1369585
median10.875419
Q314.284541
95-th percentile15.164553
Maximum15.328223
Range15.328223
Interquartile range (IQR)5.1475823

Descriptive statistics

Standard deviation4.376995
Coefficient of variation (CV)0.41670283
Kurtosis0.63462936
Mean10.503876
Median Absolute Deviation (MAD)1.9284406
Skewness-1.1448379
Sum548396.88
Variance19.158085
MonotonicityNot monotonic
2023-07-08T17:28:54.638761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2032
 
3.9%
0.01050000242 27
 
0.1%
0.0110000018 24
 
< 0.1%
0.01200000197 17
 
< 0.1%
0.01150000188 16
 
< 0.1%
8.989999771 11
 
< 0.1%
0.01450000238 8
 
< 0.1%
0.01500000246 7
 
< 0.1%
0.01300000213 7
 
< 0.1%
0.01250000205 7
 
< 0.1%
Other values (49941) 50053
95.0%
(Missing) 495
 
0.9%
ValueCountFrequency (%)
0 2032
3.9%
0.0004370000825 1
 
< 0.1%
0.002155263577 1
 
< 0.1%
0.002725000551 1
 
< 0.1%
0.005596501403 1
 
< 0.1%
0.005808000569 1
 
< 0.1%
0.006096001016 1
 
< 0.1%
0.006499501644 1
 
< 0.1%
0.007695002016 1
 
< 0.1%
0.008179502562 1
 
< 0.1%
ValueCountFrequency (%)
15.32822268 1
< 0.1%
15.32820618 1
< 0.1%
15.31717166 1
< 0.1%
15.31660791 1
< 0.1%
15.31467714 1
< 0.1%
15.31283735 1
< 0.1%
15.3102567 1
< 0.1%
15.29959698 1
< 0.1%
15.29783969 1
< 0.1%
15.29519708 1
< 0.1%

Generator RPM (RPM)
Real number (ℝ)

Distinct52204
Distinct (%)> 99.9%
Missing494
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean1246.1689
Minimum-83.908291
Maximum1816.8041
Zeros2
Zeros (%)< 0.1%
Negative682
Negative (%)1.3%
Memory size411.9 KiB
2023-07-08T17:28:54.740817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-83.908291
5-th percentile15.396014
Q11085.3517
median1290.6874
Q31693.3453
95-th percentile1797.1805
Maximum1816.8041
Range1900.7124
Interquartile range (IQR)607.99353

Descriptive statistics

Standard deviation518.28359
Coefficient of variation (CV)0.41590157
Kurtosis0.64350213
Mean1246.1689
Median Absolute Deviation (MAD)228.34462
Skewness-1.1495619
Sum65062478
Variance268617.88
MonotonicityNot monotonic
2023-07-08T17:28:54.835321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1066.942921 2
 
< 0.1%
1798.769571 2
 
< 0.1%
1798.054487 2
 
< 0.1%
1119.849976 2
 
< 0.1%
0 2
 
< 0.1%
1068.792807 2
 
< 0.1%
49.41934061 1
 
< 0.1%
75.90480244 1
 
< 0.1%
58.44703281 1
 
< 0.1%
52.05682589 1
 
< 0.1%
Other values (52194) 52194
99.0%
(Missing) 494
 
0.9%
ValueCountFrequency (%)
-83.90829126 1
< 0.1%
-82.43758472 1
< 0.1%
-47.39717252 1
< 0.1%
-27.63898623 1
< 0.1%
-15.63226249 1
< 0.1%
-1.07631214 1
< 0.1%
-1.020058933 1
< 0.1%
-0.7865775442 1
< 0.1%
-0.7412748346 1
< 0.1%
-0.7399777975 1
< 0.1%
ValueCountFrequency (%)
1816.804064 1
< 0.1%
1813.992651 1
< 0.1%
1813.496675 1
< 0.1%
1813.434071 1
< 0.1%
1813.313478 1
< 0.1%
1813.16098 1
< 0.1%
1812.821159 1
< 0.1%
1812.498035 1
< 0.1%
1812.426476 1
< 0.1%
1812.263477 1
< 0.1%
Distinct37927
Distinct (%)73.0%
Missing748
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean11.351407
Minimum-2
Maximum34.83158
Zeros0
Zeros (%)0.0%
Negative222
Negative (%)0.4%
Memory size411.9 KiB
2023-07-08T17:28:54.938843image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile3.4100001
Q17.06
median10.7
Q315.11
95-th percentile21.4725
Maximum34.83158
Range36.83158
Interquartile range (IQR)8.0500003

Descriptive statistics

Standard deviation5.6164827
Coefficient of variation (CV)0.49478296
Kurtosis0.093125738
Mean11.351407
Median Absolute Deviation (MAD)3.9950002
Skewness0.53587896
Sum589773.7
Variance31.544878
MonotonicityNot monotonic
2023-07-08T17:28:55.037163image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.5 79
 
0.1%
7.900000095 57
 
0.1%
6 57
 
0.1%
7.5 53
 
0.1%
9.199999809 52
 
0.1%
10.60000038 52
 
0.1%
11 52
 
0.1%
9.300000191 52
 
0.1%
5.400000095 50
 
0.1%
7 50
 
0.1%
Other values (37917) 51402
97.5%
(Missing) 748
 
1.4%
ValueCountFrequency (%)
-2 2
< 0.1%
-1.997500002 1
< 0.1%
-1.984999996 1
< 0.1%
-1.94749999 1
< 0.1%
-1.932499993 1
< 0.1%
-1.931578937 1
< 0.1%
-1.927499986 1
< 0.1%
-1.910000002 1
< 0.1%
-1.899999976 1
< 0.1%
-1.8875 1
< 0.1%
ValueCountFrequency (%)
34.83157971 1
< 0.1%
34.79000053 1
< 0.1%
34.60882344 1
< 0.1%
34.55 1
< 0.1%
34.35833316 1
< 0.1%
34.33157891 1
< 0.1%
34.25789482 1
< 0.1%
34.18250027 1
< 0.1%
34.01250019 1
< 0.1%
33.97749977 1
< 0.1%

Front bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39793
Distinct (%)76.6%
Missing748
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean64.956223
Minimum8.6700004
Maximum82.957501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:55.146250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum8.6700004
5-th percentile36.204999
Q162.19
median70.572501
Q373.102499
95-th percentile74.491507
Maximum82.957501
Range74.287501
Interquartile range (IQR)10.912499

Descriptive statistics

Standard deviation13.138605
Coefficient of variation (CV)0.20226861
Kurtosis4.8834159
Mean64.956223
Median Absolute Deviation (MAD)3.2749985
Skewness-2.1910122
Sum3374865.5
Variance172.62294
MonotonicityNot monotonic
2023-07-08T17:28:55.245798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.699999809 40
 
0.1%
9.5 24
 
< 0.1%
14.89999962 19
 
< 0.1%
10 19
 
< 0.1%
15 18
 
< 0.1%
12.19999981 18
 
< 0.1%
9.899999619 17
 
< 0.1%
19.39999962 17
 
< 0.1%
12.39999962 17
 
< 0.1%
13.19999981 16
 
< 0.1%
Other values (39783) 51751
98.2%
(Missing) 748
 
1.4%
ValueCountFrequency (%)
8.670000362 1
 
< 0.1%
8.800000191 3
 
< 0.1%
8.825000048 1
 
< 0.1%
8.847368341 1
 
< 0.1%
8.899999619 8
< 0.1%
8.937499809 1
 
< 0.1%
8.959999847 1
 
< 0.1%
8.972499895 1
 
< 0.1%
8.974999905 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
82.95750122 1
< 0.1%
82.77750053 1
< 0.1%
82.52000046 1
< 0.1%
82.51749992 1
< 0.1%
82.51249962 1
< 0.1%
82.49249878 1
< 0.1%
82.40294064 1
< 0.1%
82.38999977 1
< 0.1%
82.38750038 1
< 0.1%
82.38499985 1
< 0.1%

Tower Acceleration X (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct51954
Distinct (%)> 99.9%
Missing749
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean68.803204
Minimum1.7709007
Maximum265.51316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:55.349219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1.7709007
5-th percentile3.9189504
Q143.508137
median66.884819
Q394.900044
95-th percentile133.86213
Maximum265.51316
Range263.74226
Interquartile range (IQR)51.391908

Descriptive statistics

Standard deviation38.571812
Coefficient of variation (CV)0.5606107
Kurtosis-0.12096193
Mean68.803204
Median Absolute Deviation (MAD)25.57361
Skewness0.27233045
Sum3574670.4
Variance1487.7847
MonotonicityNot monotonic
2023-07-08T17:28:55.565269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.84499855 2
 
< 0.1%
127.1745586 1
 
< 0.1%
3.305494991 1
 
< 0.1%
3.580032146 1
 
< 0.1%
3.343441038 1
 
< 0.1%
3.300311153 1
 
< 0.1%
3.450479253 1
 
< 0.1%
3.556364831 1
 
< 0.1%
2.87875776 1
 
< 0.1%
3.105379611 1
 
< 0.1%
Other values (51944) 51944
98.6%
(Missing) 749
 
1.4%
ValueCountFrequency (%)
1.77090069 1
< 0.1%
1.911994539 1
< 0.1%
1.926082623 1
< 0.1%
2.00851558 1
< 0.1%
2.01698377 1
< 0.1%
2.106955031 1
< 0.1%
2.150934587 1
< 0.1%
2.153377356 1
< 0.1%
2.187041503 1
< 0.1%
2.195515538 1
< 0.1%
ValueCountFrequency (%)
265.5131622 1
< 0.1%
265.3375739 1
< 0.1%
254.7307762 1
< 0.1%
254.1732841 1
< 0.1%
251.5921803 1
< 0.1%
245.9706512 1
< 0.1%
244.4527565 1
< 0.1%
239.2045002 1
< 0.1%
234.8130943 1
< 0.1%
234.1046853 1
< 0.1%

Wind speed (m/s)
Real number (ℝ)

Distinct52109
Distinct (%)99.8%
Missing494
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean6.4319771
Minimum0
Maximum23.826238
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:55.660036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.3301928
Q14.3258998
median6.059735
Q38.1474176
95-th percentile11.74317
Maximum23.826238
Range23.826238
Interquartile range (IQR)3.8215178

Descriptive statistics

Standard deviation2.934169
Coefficient of variation (CV)0.45618462
Kurtosis0.80143496
Mean6.4319771
Median Absolute Deviation (MAD)1.8817827
Skewness0.75710206
Sum335813.52
Variance8.6093477
MonotonicityNot monotonic
2023-07-08T17:28:55.766086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.49000001 4
 
< 0.1%
5.25 3
 
< 0.1%
2.99000001 3
 
< 0.1%
6.760000229 3
 
< 0.1%
3.5 3
 
< 0.1%
2.24000001 3
 
< 0.1%
5.869999886 3
 
< 0.1%
5.868448448 2
 
< 0.1%
0 2
 
< 0.1%
5.992186069 2
 
< 0.1%
Other values (52099) 52182
99.0%
(Missing) 494
 
0.9%
ValueCountFrequency (%)
0 2
< 0.1%
0.2628751922 1
< 0.1%
0.286559308 1
< 0.1%
0.2923619477 1
< 0.1%
0.3193876874 1
< 0.1%
0.3337126605 1
< 0.1%
0.3339189589 1
< 0.1%
0.3424342926 1
< 0.1%
0.3457502332 1
< 0.1%
0.3517501146 1
< 0.1%
ValueCountFrequency (%)
23.82623816 1
< 0.1%
22.48500443 1
< 0.1%
22.12963597 1
< 0.1%
22.07687092 1
< 0.1%
21.8805913 1
< 0.1%
21.77129595 1
< 0.1%
21.7010675 1
< 0.1%
21.50505323 1
< 0.1%
21.45147181 1
< 0.1%
21.2695509 1
< 0.1%

Tower Acceleration y (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct51954
Distinct (%)> 99.9%
Missing749
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean30.645383
Minimum1.7720129
Maximum192.91374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:55.872830image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1.7720129
5-th percentile3.9693183
Q118.890117
median27.67738
Q340.255089
95-th percentile62.83575
Maximum192.91374
Range191.14173
Interquartile range (IQR)21.364973

Descriptive statistics

Standard deviation18.294281
Coefficient of variation (CV)0.59696697
Kurtosis3.9707946
Mean30.645383
Median Absolute Deviation (MAD)10.366174
Skewness1.2877005
Sum1592180.9
Variance334.68073
MonotonicityNot monotonic
2023-07-08T17:28:55.977747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.52127767 2
 
< 0.1%
33.33640196 1
 
< 0.1%
3.709229225 1
 
< 0.1%
3.56091989 1
 
< 0.1%
3.669150335 1
 
< 0.1%
3.191006577 1
 
< 0.1%
2.986392926 1
 
< 0.1%
2.877111985 1
 
< 0.1%
3.591257938 1
 
< 0.1%
3.059641369 1
 
< 0.1%
Other values (51944) 51944
98.6%
(Missing) 749
 
1.4%
ValueCountFrequency (%)
1.772012924 1
< 0.1%
2.12947719 1
< 0.1%
2.137679932 1
< 0.1%
2.151422456 1
< 0.1%
2.163078964 1
< 0.1%
2.189886621 1
< 0.1%
2.195312755 1
< 0.1%
2.20169861 1
< 0.1%
2.20834198 1
< 0.1%
2.227021363 1
< 0.1%
ValueCountFrequency (%)
192.9137411 1
< 0.1%
190.1838524 1
< 0.1%
189.368927 1
< 0.1%
180.5313692 1
< 0.1%
179.6000168 1
< 0.1%
177.0303912 1
< 0.1%
171.992018 1
< 0.1%
171.0128996 1
< 0.1%
162.0119309 1
< 0.1%
161.3990871 1
< 0.1%
Distinct22
Distinct (%)< 0.1%
Missing749
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean411.08913
Minimum401
Maximum427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.9 KiB
2023-07-08T17:28:56.077251image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum401
5-th percentile401
Q1406
median411
Q3416
95-th percentile426
Maximum427
Range26
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.3909443
Coefficient of variation (CV)0.017978934
Kurtosis-0.53583515
Mean411.08913
Median Absolute Deviation (MAD)5
Skewness0.68536333
Sum21358136
Variance54.626058
MonotonicityIncreasing
2023-07-08T17:28:56.163701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
406 12258
23.3%
411 8328
15.8%
416 4464
 
8.5%
405 4072
 
7.7%
401 3761
 
7.1%
424 3591
 
6.8%
415 3143
 
6.0%
402 1905
 
3.6%
426 1597
 
3.0%
427 1519
 
2.9%
Other values (12) 7317
13.9%
ValueCountFrequency (%)
401 3761
 
7.1%
402 1905
 
3.6%
403 449
 
0.9%
404 719
 
1.4%
405 4072
 
7.7%
406 12258
23.3%
407 132
 
0.3%
409 814
 
1.5%
410 1450
 
2.8%
411 8328
15.8%
ValueCountFrequency (%)
427 1519
 
2.9%
426 1597
 
3.0%
425 220
 
0.4%
424 3591
6.8%
423 1086
 
2.1%
418 1266
 
2.4%
417 8
 
< 0.1%
416 4464
8.5%
415 3143
6.0%
414 169
 
0.3%

Interactions

2023-07-08T17:28:51.379308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:36.285396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.535478image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.779231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.029819image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:41.216173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.571069image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.841465image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.096696image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.474172image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.721473image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.881851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.140119image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.464396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:36.363412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.624257image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.864397image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.111300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:41.306583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.659804image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.930416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.187198image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.565148image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.805708image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.963192image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.226420image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.557418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:36.456716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.721458image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.960838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.205019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:41.403737image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.760317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.027797image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.285710image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.669340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.897209image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.055947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.324737image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.652626image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:36.551957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.819228image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.055429image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.298096image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:41.507058image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.859280image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.126614image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.386272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.771686image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.986989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.145973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.420655image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.735138image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:36.633742image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.907537image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.143472image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.381213image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:41.595304image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.950745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.214955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.476278image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.866022image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.070295image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.229983image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.510624image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.827103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:36.726404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.004242image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.240322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.472399image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:41.807572image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.048096image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.311718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.690367image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.958110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.160795image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.316414image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.606429image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.923591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:36.822190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.105089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.343413image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.570471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:41.904054image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.150846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.412590image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.787836image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.057055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.259069image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.406492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.708099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:52.015455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:36.915393image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.205203image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.441902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.661639image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.001513image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.251490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.512098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.889208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.151112image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.352023image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.496558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.805045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:52.110362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.010290image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.302578image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.543796image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.754712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.097299image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.353701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.613144image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.987038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.246624image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.445864image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.584873image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.904200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:52.204844image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.106841image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.404718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.645246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.851483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.195414image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.455532image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.715800image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.085497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.342421image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.535435image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.787287image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.002341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:52.292628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.192300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.495534image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.740522image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:40.940436image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.285560image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.550094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.806258image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.176409image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.435814image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.620543image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.871506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.096367image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:52.379496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.276128image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.587466image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.833056image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:41.027519image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.376737image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.641486image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:44.898443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.273134image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.526085image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.703993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:49.956677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.186541image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:52.475289image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:37.446776image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:38.686194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:39.937042image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:41.124784image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:42.476506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:43.746378image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:45.003264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:46.377521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:47.628212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:48.795124image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:50.051237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:28:51.286582image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-07-08T17:28:56.246498image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Power (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
Power (kW)1.0000.0280.024-0.3030.6360.9870.987-0.1770.9290.6050.9030.779-0.160
Wind direction (°)0.0281.0000.9190.0060.0070.0290.029-0.0970.0230.0830.0320.0760.038
Nacelle position (°)0.0240.9191.0000.008-0.0010.0240.025-0.1000.0180.0800.0310.0700.037
blade_angle-0.3030.0060.0081.000-0.545-0.299-0.3000.101-0.367-0.175-0.170-0.084-0.008
Rear bearing temperature (°C)0.6360.007-0.001-0.5451.0000.6320.6280.1310.7590.4390.5210.441-0.028
Rotor speed (RPM)0.9870.0290.024-0.2990.6321.0000.999-0.1720.9280.6290.8820.786-0.157
Generator RPM (RPM)0.9870.0290.025-0.3000.6280.9991.000-0.1810.9280.6280.8820.786-0.159
Nacelle ambient temperature (°C)-0.177-0.097-0.1000.1010.131-0.172-0.1811.000-0.133-0.088-0.186-0.1100.146
Front bearing temperature (°C)0.9290.0230.018-0.3670.7590.9280.928-0.1331.0000.5630.8230.705-0.146
Tower Acceleration X (mm/ss)0.6050.0830.080-0.1750.4390.6290.628-0.0880.5631.0000.4810.830-0.142
Wind speed (m/s)0.9030.0320.031-0.1700.5210.8820.882-0.1860.8230.4811.0000.756-0.077
Tower Acceleration y (mm/ss)0.7790.0760.070-0.0840.4410.7860.786-0.1100.7050.8300.7561.000-0.127
Metal particle count counter-0.1600.0380.037-0.008-0.028-0.157-0.1590.146-0.146-0.142-0.077-0.1271.000

Missing values

2023-07-08T17:28:52.602375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-08T17:28:52.800065image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-07-08T17:28:53.032571image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
02020-01-01 00:00:00231.945189112.719236102.1921540.29849865.7675009.7992971164.4530546.31000066.332500127.1745594.77216633.336402401.0
12020-01-01 00:10:00140.533767111.551353102.1921540.67266664.5025009.5590591136.8054736.38750064.14500084.7688154.15908338.985235401.0
22020-01-01 00:20:00107.840487114.731451102.1921541.01466763.6475009.5638881136.9422196.16000062.37000087.9325933.91791936.168087401.0
32020-01-01 00:30:0098.657917105.735526102.1921541.02083363.2975009.3706671114.1561055.94000061.66499999.9119793.70545331.876746401.0
42020-01-01 00:40:0084.125479118.384276102.1921541.05933462.7775019.3180441108.6100235.94000060.85250082.4589823.61369936.153631401.0
52020-01-01 00:50:00228.341178136.564793115.3408730.41499663.7611119.8720791173.9067976.27222261.96944495.5733814.47424427.316749401.0
62020-01-01 01:00:00469.897940139.840190140.6067350.00000067.51250111.2579121337.3085946.36750067.77500076.9829026.02843928.625906401.0
72020-01-01 01:10:00311.834909140.347064140.6067350.02483367.19749910.0671931195.7455966.38000068.43000082.0089555.15874836.557546401.0
82020-01-01 01:20:00255.473336140.833146140.6067350.04866666.3275019.7478921158.7605466.35000067.177501105.2793584.60280142.721662401.0
92020-01-01 01:30:00319.056814140.966290140.6067350.00000067.02500110.1066651201.6865506.35250067.86999966.9266125.33488833.061149401.0
# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
526942020-12-31 22:20:00369.463979313.921116321.7030940.064.96500110.4723841245.1157511.355065.98500028.9858136.00670211.567844427.0
526952020-12-31 22:30:00361.732513311.734085321.7030940.065.18250010.3948551235.2571581.375066.63500130.9153645.90555511.202269427.0
526962020-12-31 22:40:00251.036552302.945341309.7126080.063.9125019.4725841125.5956481.385065.12250023.8440955.10935414.298858427.0
526972020-12-31 22:50:00222.886928299.404388292.0688480.063.0275019.1540991089.0131031.577563.65000118.3339425.0894178.572872427.0
526982020-12-31 23:00:00234.225565302.304094292.0688480.063.8250019.2167221095.5431081.605064.38000013.2933305.13482110.972044427.0
526992020-12-31 23:10:00197.851878301.953930292.0688480.063.2550019.0250351073.9435811.612563.87000112.9758614.6761796.896102427.0
527002020-12-31 23:20:00169.289626302.223245292.0688480.062.3500008.9931331070.6129321.692562.40750116.1089264.5970847.938308427.0
527012020-12-31 23:30:00185.616846297.672479292.0688480.062.2675008.9942881070.4686511.700062.11000013.6039434.7313108.319322427.0
527022020-12-31 23:40:00174.596239293.269840292.0688480.062.1550008.9898961070.2777061.760061.85500011.2582654.5641366.720812427.0
527032020-12-31 23:50:00276.021474303.753617292.0688480.063.0525009.7486511158.8039071.630062.86749915.4835355.2078839.896075427.0